Civil infrastructure (eg, buildings, roads, underground tunnels) could lose its expected
physical and functional conditions after years of operation. Timely and accurate inspection …

Data scarcity is a major challenge when training deep learning (DL) models. DL demands a
large amount of data to achieve exceptional performance. Unfortunately, many applications …

The intelligent detection of pavement distress using deep learning methods has consistently
been a hotspot in pavement maintenance. This paper aims to offer new insights to promote …

Pavements function as protective layers for roads and require frequent inspection and
maintenance throughout their service life. This paper describes an intelligent pavement …

Automatic monitoring of pavement structure health has always been a significant problem for
transportation engineers. Although the generative adversarial network (GAN) has proven to …

Monitoring of critical infrastructure for Structural Health Monitoring (SHM) is vital for the
detection of structural damage (cracks or voids) at an initial stage, thus increasing the …

In the design evolution of a product, designers often require solving similar functions
repeatedly across different designs. These functions are usually related to each other and …

Due to the rapid advancement of the transportation industry and the continual increase in
pavement infrastructure, it is difficult to keep up with the huge road maintenance task by …

In response to the critical need for rapid post-disaster assessments, this paper introduces an
innovative application of artificial intelligence (AI) in Unmanned Aerial Vehicles (UAVs) for …

Concrete bridges are susceptible to surface damage such as water-corrosion, spalling, and
rebar-corrosion, which can pose serious safety risks, and to detect this is crucial to ensure …